update docstring

dmlc · Oct 12, 2023 · 19b9269 · 19b9269
1 parent 1d2be42
commit 19b9269
Showing 1 changed file with 18 additions and 22 deletions.
diff --git a/python/dgl/data/lrgb.py b/python/dgl/data/lrgb.py
@@ -283,9 +283,7 @@ def __getitem__(self, idx):
                 return Subset(self, idx.cpu())
 
             raise ValueError(
-                """
-                    Not support tensor idx when transform is not None
-                    """
+                "Tensor idx not supported when transform is not None."
             )
 
         if self._transform is None:
@@ -533,9 +531,7 @@ def __getitem__(self, idx):
                 return Subset(self, idx.cpu())
 
             raise ValueError(
-                """
-                    Not support tensor idx when transform is not None
-                    """
+                "Tensor idx not supported when transform is not None."
             )
 
         if self._transform is None:
@@ -577,14 +573,16 @@ class VOCSuperpixelsDataset(DGLDataset):
     construct_format : str, optional
         Option to select the graph construction format.
         Should be chosen from the following formats:
-        "edge_wt_only_coord": the graphs are 8-nn graphs with the edge weights
-        computed based on only spatial coordinates of superpixel nodes.
-        "edge_wt_coord_feat": the graphs are 8-nn graphs with the edge weights
-        computed based on combination of spatial coordinates and feature
-        values of superpixel nodes.
-        "edge_wt_region_boundary": the graphs region boundary graphs where two
-        regions (i.e. superpixel nodes) have an edge between them if they share
-        a boundary in the original image.
+
+        - "edge_wt_only_coord": the graphs are 8-nn graphs with the edge weights
+          computed based on only spatial coordinates of superpixel nodes.
+        - "edge_wt_coord_feat": the graphs are 8-nn graphs with the edge weights
+          computed based on combination of spatial coordinates and feature
+          values of superpixel nodes.
+        - "edge_wt_region_boundary": the graphs region boundary graphs where two
+          regions (i.e. superpixel nodes) have an edge between them if they
+          share a boundary in the original image.
+
         Default: "edge_wt_region_boundary".
     slic_compactness : int, optional
         Option to select compactness of slic that was used for superpixels
@@ -792,9 +790,7 @@ def __getitem__(self, idx):
                 return Subset(self, idx.cpu())
 
             raise ValueError(
-                """
-                Not support tensor idx when transform is not None
-                """
+                "Tensor idx not supported when transform is not None."
             )
 
         if self._transform is None:
@@ -806,8 +802,8 @@ def __getitem__(self, idx):
 class COCOSuperpixelsDataset(DGLDataset):
     r"""COCO superpixel dataset for the node classification task.
 
-    DGL dataset of COCOSuperpixels which contains image superpixels
-    and a semantic segmentation label for each node superpixel.
+    DGL dataset of COCO-SP in the LRGB benckmark which contains image
+    superpixels and a semantic segmentation label for each node superpixel.
 
     Based on the COCO 2017 dataset. Original source `<https://cocodataset.org>`_
 
@@ -833,6 +829,7 @@ class COCOSuperpixelsDataset(DGLDataset):
     construct_format : str, optional
         Option to select the graph construction format.
         Should be chosen from the following formats:
+
         - "edge_wt_only_coord": the graphs are 8-nn graphs with the edge weights
           computed based on only spatial coordinates of superpixel nodes.
         - "edge_wt_coord_feat": the graphs are 8-nn graphs with the edge weights
@@ -841,6 +838,7 @@ class COCOSuperpixelsDataset(DGLDataset):
         - "edge_wt_region_boundary": the graphs region boundary graphs where two
           regions (i.e. superpixel nodes) have an edge between them if they
           share a boundary in the original image.
+
         Default: "edge_wt_region_boundary".
     slic_compactness : int, optional
         Option to select compactness of slic that was used for superpixels
@@ -1075,9 +1073,7 @@ def __getitem__(self, idx):
             if self._transform is None:
                 return Subset(self, idx.cpu())
             raise ValueError(
-                """
-                    Tensor idx not supported when transform is not None.
-                    """
+                "Tensor idx not supported when transform is not None."
             )
 
         if self._transform is None: